docstr: Compares the outputs of `iterative_closest_point` with the results
  of `trimesh.registration.icp` from the `trimesh` python package:
  https://github.com/mikedh/trimesh
  
  We have run `trimesh.registration.icp` on several random problems
  with different point cloud sizes. The results of trimesh, together with
  the randomly generated input clouds are loaded in the constructor of
  this class and this test compares the loaded results to our runs.
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code: def test_compare_with_trimesh(self):
      """
      Compares the outputs of `iterative_closest_point` with the results
      of `trimesh.registration.icp` from the `trimesh` python package:
      https://github.com/mikedh/trimesh
  
      We have run `trimesh.registration.icp` on several random problems
      with different point cloud sizes. The results of trimesh, together with
      the randomly generated input clouds are loaded in the constructor of
      this class and this test compares the loaded results to our runs.
      """
      for n_points_X in (10, 20, 50, 100):
          for n_points_Y in (10, 20, 50, 100):
              self._compare_with_trimesh(
                  n_points_X=n_points_X, n_points_Y=n_points_Y
              )
  
imports: import unittest
  import numpy
  import torch
  from pytorch3d.ops import points_alignment
  from pytorch3d.structures.pointclouds import Pointclouds
  from pytorch3d.transforms import rotation_conversions
  from .common_testing import get_tests_dir, TestCaseMixin
label_desc: Use image node_id 5 for calling the TestICP obj's underlying member method code with example usage: obj.test_compare_with_trimesh() without return types